Critical infrastructures are important national assets for producing or distributing continuous flows of essential goods or services. When one critical infrastructure shuts down due to an external disruption, it can be expected that other critical infrastructures that need goods or services provided by the discontinued one will stop shortly, exacerbating the damage caused by the external disruption. Past research has categorized critical infrastructure interdependency (CII) into four relationship types and has proposed several methods to model CII and its effects. This paper presents a knowledge discovery process for CII that can be used to extract frequent patterns of critical infrastructure failure records directly or indirectly triggered by external disruptions. The knowledge discovery process, including integration of critical infrastructure failure records and transformation into the data format needed by the data mining algorithm, is described. Discussion of a disaster mitigation approach to stopping CII-related possible future failure events is addressed, followed by the analysis results of sample critical infrastructure failure records. Disaster mitigation officials can employ the proposed approach to explore CII and to design countermeasures when a disaster hits certain areas.